Alexander Mandl

According to our database, Alexander Mandl authored at least 17 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

On reducing the amount of samples required for training of QNNs: constraints on the linear structure of the training data.

Alexander Mandl, Johanna Barzen, Frank Leymann, Daniel Vietz

Quantum Mach. Intell., December, 2025

Data repository for "Simulating Quantum State Transfer between Distributed Devices using Noisy Interconnects".

Marvin Bechtold, Johanna Barzen, Frank Leymann, Alexander Mandl

Dataset, October, 2025

Data repository for "Loss Behavior in Supervised Learning With Entangled States".

Alexander Mandl, Johanna Barzen, Marvin Bechtold, Frank Leymann, Lavinia Stiliadou

Dataset, September, 2025

Data repository for "Simulating Quantum State Transfer between Distributed Devices using Noisy Interconnects".

Marvin Bechtold, Johanna Barzen, Frank Leymann, Alexander Mandl

Dataset, July, 2025

2024

Data repository for "Joint Wire Cutting with Non-Maximally Entangled States".

Marvin Bechtold, Johanna Barzen, Frank Leymann, Alexander Mandl, Felix Truger

Dataset, December, 2024

Data repository for "Minimial-Risk Training Samples for QNN Training from Measurements".

Alexander Mandl, Marvin Bechtold, Johanna Barzen, Frank Leymann

Dataset, October, 2024

Warm-Starting and Quantum Computing: A Systematic Mapping Study.

Felix Truger, Johanna Barzen, Marvin Bechtold, Martin Beisel, Frank Leymann, Alexander Mandl, Vladimir Yussupov

ACM Comput. Surv., September, 2024

Data repository for: Cutting a Wire with Non-Maximally Entangled States.

Marvin Bechtold, Johanna Barzen, Frank Leymann, Alexander Mandl

Dataset, January, 2024

Exploring the Cost Landscape of Variational Quantum Algorithms.

Lavinia Stiliadou, Johanna Barzen, Frank Leymann, Alexander Mandl, Benjamin Weder

Proceedings of the Service-Oriented Computing - 18th Symposium and Summer School, 2024

Minimial-Risk Training Samples for QNN Training from Measurements.

Alexander Mandl, Johanna Barzen, Marvin Bechtold, Frank Leymann

Proceedings of the Service-Oriented Computing - 18th Symposium and Summer School, 2024

Cutting a Wire with Non-Maximally Entangled States.

Marvin Bechtold, Johanna Barzen, Frank Leymann, Alexander Mandl

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2024

2023

Reproduction Code for: On Reducing the Amount of Samples Required for Training of QNNs.

Alexander Mandl, Johanna Barzen, Frank Leymann, Victoria Mangold, Benedikt Riegel, Daniel Vietz, Felix Winterhalter

Dataset, September, 2023

Data Repository for: On Reducing the Amount of Samples Required for Training of QNNs.

Alexander Mandl, Johanna Barzen, Frank Leymann, Victoria Mangold, Benedikt Riegel, Daniel Vietz, Felix Winterhalter

Dataset, September, 2023

Data repository for: Investigating the effect of circuit cutting in QAOA for the MaxCut problem on NISQ devices.

Marvin Bechtold, Johanna Barzen, Frank Leymann, Alexander Mandl, Julian Obst, Felix Truger, Benjamin Weder

Dataset, July, 2023

Data Repository for a Systematic Mapping Study on Warm-Starting and Quantum Computing.

Felix Truger, Johanna Barzen, Marvin Bechtold, Martin Beisel, Frank Leymann, Alexander Mandl, Vladimir Yussupov

Dataset, March, 2023

Linear Structure of Training Samples in Quantum Neural Network Applications.

Alexander Mandl, Johanna Barzen, Marvin Bechtold, Michael Keckeisen, Frank Leymann, Patrick K. S. Vaudrevange

Proceedings of the Service-Oriented Computing - ICSOC 2023 Workshops - AI-PA, ASOCA, SAPD, SQS, SSCOPE, WESOACS and Satellite Events, Rome, Italy, November 28, 2023

2022

Implementations for Shor's algorithm for the DLP.

Alexander Mandl, Uwe Egly

Proceedings of the 52. Jahrestagung der Gesellschaft für Informatik, INFORMATIK 2022, Informatik in den Naturwissenschaften, 26., 2022